Gas processing pipelines are central to gas monetisation and power stability in Ghana, yet peer reviewed evidence on their corrosion behaviour remains limited compared with global literature. The regional operating environment combines internal wet gas CO2 and H2S attack with marine atmospheric corrosion, corrosion under insulation and buried coating failure, creating multi mechanism degradation that cannot be represented by single gas intuition or average rate models alone. At the same time, monitoring and predictive modelling have moved toward layered sensing architectures and probabilistic, machine learning and hybrid approaches, although many studies rely on simulated data, weak validation and incomplete uncertainty treatment, which reduces confidence for safety critical deployment. Using a structured narrative review with scoping features and conservative inclusion criteria, this article examines corrosion mechanisms, monitoring techniques, predictive models and the limited Ghana and Sub Saharan specific evidence base. The review finds that model transfer without regional calibration is unsafe and that monitoring must be designed around deployability as much as technical capability. It proposes a research programme focused on long term regional datasets, systematic recalibration of transferable oil-sector and analogue marine evidence, hybrid mechanistic-data driven models with explicit uncertainty quantification, field validation under tropical coastal and onshore gas conditions, and open yet secure data structures and capacity building to support defensible integrity decisions in Ghanaian and Sub Saharan gas processing networks.